Triple
T33565526
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | El príncipe constante |
E859746
|
entity |
| Predicate | religiousAffiliationOfProtagonist |
P83945
|
FINISHED |
| Object | Christianity |
—
|
NE NERFINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Christianity | Statement: [El príncipe constante, religiousAffiliationOfProtagonist, Christianity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: religiousAffiliationOfProtagonist Context triple: [El príncipe constante, religiousAffiliationOfProtagonist, Christianity]
-
A.
religionOfCharacterPortrayed
chosen
Indicates that a work portrays a character as adhering to or being associated with a particular religion.
-
B.
religiousAffiliation
Indicates that one entity has a specified religious association, belief system, or denominational membership.
-
C.
creatorReligiousAffiliation
Indicates the religious affiliation or tradition with which a creator is associated.
-
D.
hostReligion
Indicates that an entity organizes, accommodates, or provides a venue for a particular religious group, event, or practice.
-
E.
religiousTarget
Indicates that an action, policy, or behavior is directed at someone or something specifically because of their religion or religious affiliation.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69f3497c1d288190a844ea699914e038 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69ff27b125948190aced0fe0189fd39a |
completed | May 9, 2026, 12:25 p.m. |
| PD | Predicate disambiguation | batch_69ff26c30a0481909ef6a54ded851e42 |
completed | May 9, 2026, 12:21 p.m. |
Created at: May 1, 2026, 1:40 a.m.